9 Remote Entry-level Data Engineer Jobs (No Experience Required)
Explore flexible and work from home entry-level data engineer positions available worldwide. Your career in truly remote companies - apply today.
People also searched for:
junior data engineer jobsanalytics engineer jobsproduct analyst jobsdata architect jobs
12 hours ago
Bayer
10,000+
Join Bayer as an Intern: Data Engineer in Digital Farming Work on data infrastructure and insights for sustainable agriculture solutions
🇺🇸 United States – Remote
💵 $20 - $30 / hour
💰 Grant on 2022-11
👨🎓 Internship
⚪️ Entry-level
🚰 Data Engineer
🗽 H1B Visa Sponsor
November 11
Radian
1001 - 5000
Data Engineering Intern at Radian working on software products.
November 8
Raft
51 - 200
Data Engineering Intern enhancing Data Fabric with open-source datasets at Raft.
November 1
GEICO
10,000+
Engineer at GEICO building high-performance data platforms and applications.
Top companies hiring remote entry-level data engineers
Radian
Mortgage Insurance • Loss Management and Homeownership Preservation • Risk Management
1001 - 5000
Job Openings
Remote data engineer salary expectations
The average salary for remote data engineers is $139,967 per year. This is based on data from 1,315 job openings.
Our advanced AI searches the internet for remote job openings and posts them on our website. We use the salary data from these job postings to calculate data engineer salaries.
Below is a breakdown of salary data by years of experience:
| Experience | Number of roles analyzed | Average Salary |
|---|---|---|
⚪️ Entry-level Data Engineer (0 yrs) | 2 | $99,750 |
🟢 Junior Data Engineer (1-2 yrs) | 50 | $93,580 |
🟡 Mid-level Data Engineer (2-4 yrs) | 336 | $124,295 |
🟠 Senior Data Engineer (5-9 yrs) | 796 | $141,548 |
🔴 Lead Data Engineer (10+ yrs) | 131 | $188,874 |
Frequently asked questions
You need proficiency in programming languages like Python or Java, knowledge of SQL, data modeling, and ETL processes. Familiarity with cloud platforms (e.g., AWS, Azure) and basic understanding of big data technologies (e.g., Spark, Hadoop) are also helpful. Analytical skills and attention to detail are essential.
Typically, a degree in computer science, information technology, or a related field is required. Some employers may accept relevant certifications or practical experience. A strong foundation in databases and programming is crucial.
Responsibilities include collecting and processing data from various sources, building and maintaining data pipelines, ensuring data quality, and collaborating with data scientists and analysts to meet data needs. You'll also document processes and assist in troubleshooting data issues.
Benefits include flexible work arrangements, opportunities for continuous learning, reduced commuting time, and potential for career advancement in a growing field. Remote work allows for collaboration with global teams and work-life balance.